Center for Human Performance and Sensor Applications–(CHPSA)

WELCOME

MissionCHPSA will conduct research in the areas of human performance and sensor development and applications leading to rapid prototyping of technologies critically needed by the Air Force, and train a diversified workforce in advance fields of human effectiveness and sensor technologies.

VisionCHPSA will enhance the research of faculty at Central State University in the areas of human performance and sensor technology through existing and new partnerships provided by the CHPSA, thereby, enhancing Central State University’s development as a leading research institution in the Miami Valley region, while providing additional career pathways to CSU students in the areas of human performance and sensor technologies

GoalsConduct research in the areas of human performance and sensor development and applications leading to rapid prototyping technologies critically needed by the Air Force, and train a diversified workforce in the advance fields of human effectiveness and sensor projects

Objectives

Conduct research in the areas of human performance and sensor development to develop algorithms for human motion analysis and multi-scale human motion tracking, and develop advance technologies on sensor fusion and layered sensing applications

Develop the research portfolio of CSU faculty so that they become established researchers in their field

Collaborate with neighboring institutions and organizations to advance research goals

Train, mentor, and advise undergraduate (20) and graduate students in these research areas

Collaborate with neighboring institutions to create graduate opportunities for CSU students

Conduct community outreach in K-12 to disseminate research findings

Four Projects Funded in CHPSA

Deterministic Modeling Using Algebraic Techniques: Using Groebner Basis Theory to Identify and Isolate Gait Signatures. By finding all possible joint configurations (upper and lower extremities) for an individual's gait, the position and orientation of the wrist and ankle during the gait cycle can be found. This project aims through deterministic modeling to identify and isolate signatures in the gait cycle to determine suspicious individuals.

Multi-scale Human Motion Analysis: This project proposes a multi-scale analysis framework to detect, track, understand and evaluate human activity, and crowd behaviors through surveillance camera data. Different from previous work, this project is dedicated to disclose a suspicious individual or group from a crowd of people that are under surveillance.

Wavelet Analysis Data Fusion & Target Detection: Analyzing and modeling the impacts of climatic change on irrigated agriculture. The project aims to study the land cover/land use change of irrigation agriculture districts from historical Landsat satellite imagery using image classification and change detection algorithms; and to investigate the causes and effects of climatic change on irrigated agriculture using spatial models and regional climatic models.

Algorithm Development for Facial Recognition of Workload through Wavelet Analysis: This project will focus on utilizing non-invasive techniques to conduct human facial image analysis and recognition through use of data fusion techniques, photogrammetry, and neural network techniques with the goal of identifying facial/physical biometric signatures that are a result of mental workload (i.e., stress and fatigue).